How Is Artificial Intelligence Stimulating A New Medical Sciences Revolution? (original) (raw)

Long before 2020, US and the whole world were facing a severe Health crisis. Unfortunately, this health crisis has been amplified with the COVID-19 pandemic. Fortunately, the rise of AI-driven Innovation could stimulate an AI-assisted Diagnostic Imaging Revolution that in turn could shape, structure and support the Medical Sciences Revolution of the 21st century. In fact, the ' Computer Assisted Diagnosis Radiology ' can detect and prevent the Urban-related Diseases on the one hand and facilitate their treatment on the second hand. Accordingly, studies found that a ' Computer Assisted Diagnosis Radiology ' can optimize staffing, reduce scanner time, and decrease radiation dosing for the patient. Furthermore, according to Oren, Ohad and al. (2020), the AI in radiology will improve the performance to facilitate detection and quantification of a wide array of clinical conditions. Moreover, according to Kendall Hall and Eleanor Fitall (2020), the use of AI in radiology has the potential to improve the efficiency and efficacy of medical imaging. Its use may also alleviate some of the burden and burnout experienced by radiologists who feel overwhelming by the proliferation in the volume of imaging studies performed and unable to devote sufficient time to providing meaningful, patient-centric care. This means that beyond the prevention, detection and treatment of Urban-related Diseases on the one hand and the rise of the productivity of the Radiologists on the second hand, the AI-assisted Diagnostic Imaging Revolution will improve the efficiency of the Patient-centric Care Model on the one hand and accelerate its adoption on the second hand. In fact, according to Davenport T. and Kalakota R. (2019), in healthcare, AI is currently applied in diagnostics, population health management, patient engagement, patient adherence promotion, and in administrative activities. Furthermore, according to Kendall Hall and Eleanor Fitall (2020) , once the imaging study has been conducted, AI systems can help ensure continuity in provider communication and patient care. Moreover, Davenport T. and Kalakota R. (2019) found that in some instances, AI may even predict which treatment protocols are most likely to be successful. For example, according to Souquet J. (2018), AI can review patient records to ensure that an imaging diagnosis is correlated with the radiological reports and that there is an associated treatment plan. However, regarding the limits of ' Computer Assisted Diagnosis Radiology ', Oren, Ohad and al. (2020) has suggested that as the occurrence of clinically meaningful events-symptoms, need for disease-modifying therapy, and mortality-strongly affect quality of life, the AI-based investigations should prioritize it (Patient's Quality of Life). Since then, AI-driven Innovations have started to go beyond the case of ' AI-assisted Diagnostic Imaging Revolution and target some Forward Approach that can help eradicate Urban-related Diseases. Furthermore, AI-driven Innovations are also focusing on the eradication of the Medical Errors and Hospital-acquired Infections on the one hand and the improvement of the ' Safety Management In The Time of Crisis' on the second hand. However, in order to help the New Medical Sciences Revolution to bear all the fruits expected, it's relevant to put into place an effective Cybersecurity framework in order to minimize the risk of cyberattacks that can destabilize the whole medical system in the context of New Medical Science Revolution. In factresearchers from the University of Minnesota Public Health who focused on the trends in ransomware attacks on US hospitals, clinics and other healthcare delivery organizations from 2016 to 2021 (Neprash et al., 2022) found that: - From 2016 to 2021, the annual number of ransomware attacks more than doubled from 43 to 91. - Almost half, or 44.4% of the cohort, disrupted the delivery of healthcare. - Thirty-two attacks, or 8.6% of the cohort, led to operations disruptions of more than two weeks. - Approximately one in five (20.6%) of healthcare organizations reported being able to restore data from backups. Common disruptions included electronic system downtime, 41.7%, cancellations of scheduled care, 10.2%, and ambulance diversion 4.3%. Secondly, according to Coleman-Lochner (2023), Cyberattacks on US hospitals are on the rise, adding a layer of financial pressure onto an industry still struggling to recover from thepandemic. Furthermore, according to John Riggi, the national advisor for cybersecurity and risk at the American Hospital Association, health facilities have been hit with 226 digital incursions affecting 36 million people in 2023 (From January 2023 to June 23, 2023), on track to be more widespread than 2022 attacks. Key Words: Health Crisis; COVID-19 Pandemic; AI-assisted Diagnostic Imaging Revolution; Medical Sciences Revolution ; Computer Assisted Diagnosis Radiology; Detection, Prevention; Treatment; Urban-related Diseases; Optimization of Staff; Reduction of Scanner Time; Decrease Radiation Dosing For Patients; Patient-centric Care Model; Treatment Plan; AI-based Investigations ; Forward Approach; Medical Errors; Hospital-acquired Infections; Safety Management In Time of Crisis.